• Bulletin of the Korean Chemical Society
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• v.18 no.5
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• pp.478-484
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• 1997

In a recent paper[Bull. Kor. Chem. Soc. 17, 735 (1996)] we reported results of molecular dynamic (MD) simulations for the thermodynamic and structural properties of liquid n-alkanes, from n-butane to n-heptadecane, using three different models. Two of the three classes of models are collapsed atomic models while the third class is an atomistically detailed model. In the present paper we present results of MD simulations for the dynamic properties of liquid n-alkanes using the same models. The agreement of two self-diffusion coefficients of liquid n-alkanes calculated from the mean square displacements (MSD) via the Einstein equation and the velocity auto-correlation (VAC) functions via the Green-Kubo relation is excellent. The viscosities of n-butane to n-nonane calculated from the stress auto-correlation (SAC) functions and the thermal conductivities of n-pentane to n-decane calculated from the heat-flux auto-correlation (HFAC) functions via the Green-Kubo relations are smaller than the experimental values by approximately a factor of 2 and 4, respectively.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.703-710
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• 2010

In this paper, an overload detecting algorithm for an excavator is presented. The proposed overload detecting algorithm is based on the time series analysis especially correlation function. The main purpose of this paper is to prevent damage or crack from the fatigue loaded on an excavator in advance. Generally, the larger data, the longer processing time, and the amount of the data used in this paper are also large, especially every sampling period, 1600 data are gathered and calculated. So this paper focuses on minimizing the number of required sensors by using the correlation function. From the cross correlation function, similar pattern sensors are eliminated and dissimilar pattern sensors are considered, and from the auto correlation function, the overload can be detected. To prove the efficiency of the proposed overload detecting algorithm, this paper shows the computer simulation results.

• 전자공학회논문지 IE
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• v.44 no.4
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• pp.41-47
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• 2007

In this paper, the performance of simulation model in mobile to mobile Rayleigh and Rician fading channel is analyzed and simulation results are compared. The auto-correlation and cross-correlation functions of Rayleigh fading channels not only based on received signals of Clarke's fading model and but also based on received signals of phase shifted Clarke's fading model are derived and their simulation results are found. The two models are also applied to mobile to mobile Rician fading channel models and their numerical results of auto-correlation functions of complex envelop received signals shows the statistical properties match the theoretical values very well and rapidly converge with the small number such as N=8.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.9
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• pp.995-1004
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• 2010

In the channel-varying environment, it is very important to estimate the signal to noise ratio(SNR) of received signal and to transmit the signal effectively for the modern communication system. The performance of existing non-data-aided (NDA) SNR estimation methods are substantially degraded for high level modulation scheme such as M-ary APSK or QAM. In this paper, we propose a SNR estimation method which uses zero point auto-correlation of received signal per block and auto-/cross- correlation of decision feedback signal in OFDM system. Proposed method can be studied into two Types; Type 1 can estimate SNR by zero point auto-correlation of decision feedback signal based on the second moment property. Type 2 uses both zero point auto-correlation and cross-correlation based on the fourth moment property. In block-by-block reception of OFDM system, these two SNR estimation methods can be possible for the practical implementation due to correlation based the estimation method and they show more stable estimation performance than the previous SNR estimation methods. Also, we mathematically derive the SNR estimation expression according to computational difference of auto-/cross-correlation. Finally, Monte Carlo simulations are used to verify the proposed method.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1491-1495
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• 2023

This study utilized automated machine learning (AutoML) to calculate Arctic ice surface temperature (IST). AutoML-derived IST exhibited a strong correlation coefficient (R) of 0.97 and a root mean squared error (RMSE) of 2.51K. Comparative analysis with deep neural network (DNN) models revealed that AutoML IST demonstrated good accuracy, particularly when compared to Moderate Resolution Imaging Spectroradiometer (MODIS) IST and ice mass balance (IMB) buoy IST. These findings underscore the effectiveness of AutoML in enhancing IST estimation accuracy under challenging polar conditions.

• Journal of Korean Society for Atmospheric Environment
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• v.9 no.3
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• pp.183-190
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• 1993

For the efficient control of photochemical smog materials, the researches on the change patterns of photochemical smog precursors are indispensable. In this study, a time-series analysis was performed for the auto-monitoring data of Kwanghwamun and Jamsil stations in 1990, and the change patterns of photochemical smog materials were studied. Especially, auto-correlation coefficients were analyzed to investigate the cyclic characteristics of pollutants in question and cross-correlation coefficients to investigate the correlations between pollutants adjusted for time lag and between $O_3$ and meteorological factors. Results of researches are as follows: First, in the case of NO and $NO_2$ intimately related to human activities, 12-hour cycle was prevalent. But $O_3$ showed 24-hour cycle. Second, NO showed a relatively high correlation with $O_3$ and usually developed into $O_3$ 5 to 7 hours later. Third, temperature, insolation intensity, and wind speed showed a positive correlation with $O_3$ while relative humidity a negative correlation.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1882-1885
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• 2002

This paper shows design of maximal-period sequences with prescribed constant auto-correlation values based on one-dimensional (1-D) maps with (mite bits. We construct such 1-D maps based on piecewise linear onto chaotic maps. Theoretical analyses and some design examples are given.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.11
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• pp.5557-5562
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• 2012

Aim: The aim of this study was to investigate the frequency and correlation between auto-antibodies to survivin and MUC1 variable number tandem repeats (VNTR) in colorectal cancer (CRC), which can provide valuable information for the design of immunotherapeutic vaccines for this disease. Methods: Enzyme-linked immunosorbent assays (ELISA) were used to examine the level of auto-antibodies against survivin and MUC1 VNTR in the serum of 135 CRC patients and 95 healthy volunteers. Results: Using mean absorbance + 2 standard deviations (SD) of the healthy samples as a cut-off value, the positive rates of survivin and MUC1 VNTR auto-antibodies in CRC were 31.1% and 18.5%, respectively. Altogether, the survivin and MUC1 VNTR positive samples accounted for 36.3% of the CRC patients, and 7.4% were positive for both. Conclusion: A significant positive correlation was found between levels of specific antibodies against survivin and MUC1 VNTR in the serum of CRC patients (r = 0.3652, P < 0.0001), suggesting that vaccines against both targets would elicit immune responses more effectively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.105-110
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• 2012

The CCA (canonical correlation analysis) is a well known analysis tool that measures the linear relationship between two variable sets and it can be used for blind source separation (BSS). In previous works, a blind source separation scheme based on the CCA and auto regression was proposed. Unfortunately, the proposed scheme requires high signal-to-noise ratio for successful source separation. In this paper, we propose an improved BSS scheme based on the CCA and auto regression by eliminating the main diagonal elements of auto covariance matrix. Compared to the previously proposed BSS scheme, the proposed BSS scheme not only offers better source separation performance but also requires low computational complexity.

• Journal of Animal Science and Technology
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• v.64 no.1
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• pp.135-142
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• 2022

It is impossible to know the amount of pork primal cut by pig carcass grade which is determined only by carcass weight and backfat thickness in the Korean Pig Carcass System. The aim of this study was to investigate the correlation between the pig carcass grade and the amount of pork primal cut estimated with AutoFom III. A total of 419,321 Landrace, Yorkshire, and Duroc (LYD) pigs were graded with the Korean Pig Carcass Grade System. Amounts of belly, neck, loin, tenderloin, spare ribs, shoulder, and ham were estimated with AutoFom III. Regression equations for seven primal cuts according to each grade were derived. There were significant differences among the three carcass grades due to heteroscedasticity variance (p < 0.0001). Three regression equations were derived from AutoFom III estimation of primal cuts according to carcass grades. The coefficient of determination of the regression equation was 0.941 for grade 1⁺, 0.982 for grade 1, and 0.993 for grade 2. Regression equations obtained from this study are suitable for AutoFom III software, a useful tool for the analysis of each pig carcass grade in the Korean Pig Carcass Grade System. The high reliability of predicting the amount of primal cut with AutoFom III is advantageous for the management of slaughterhouses to optimize their product sorting in Korea.